文章摘要
Data platforms are critical for the success of AI agents and the Model Context Protocol (MCP), enabling AI to access and process high-quality, real-time contextual information.
- AI agents require extensive context from various data sources, including enterprise applications, internal systems, and external APIs, to perform complex tasks effectively.
- MCP relies on robust data infrastructure to provide structured, relevant, and continuously updated context to large language models (LLMs), ensuring more accurate and reliable responses.
- Key components of a supportive data platform include data integration, vector databases for semantic search, real-time data pipelines, and strong data governance.
- Investing in a comprehensive data platform is essential for organizations to scale AI agent deployments, improve model performance, and achieve the full potential of AI-driven automation.